Working in Google Colab

Last updated on 2026-07-15 | Edit this page

Overview

Questions

  • Which packages does this lesson need installed in Colab, and how do you install them?
  • How do you read a CMS Open Data file directly from CERN without downloading it?
  • Which three files does this lesson use, and how do you check a stream actually worked?

Objectives

  • Install the packages this lesson needs inside a Google Colab notebook.
  • Open a CMS Open Data file directly from CERN using uproot, without downloading it first.
  • Identify the three files this lesson uses and confirm a stream opened correctly.

Installing the packages this lesson needs

If you followed Setup, you likely already ran this install command once. Running it again here is a quick, harmless verification that everything is still in place before moving on - pip just confirms the packages are installed and does nothing if they already are.

Colab comes with many common data science packages already installed, including numpy, pandas, matplotlib, seaborn, scikit-learn, and torch. It does not come with uproot (for reading ROOT files), fsspec-xrootd (for streaming those files over the network - without it, opening a root:// URL below fails immediately), awkward (for handling data where different events can have different numbers of particles), and vector (for particle four-vectors). Run this in a Colab cell before anything else in this lesson:

PYTHON 

!pip install uproot fsspec-xrootd awkward vector numpy torch scikit-learn matplotlib seaborn pandas

Reading files directly from CERN

CMS Open Data files live on CERN’s servers and can be streamed straight into uproot over a network protocol called xrootd, instead of being downloaded first. Hand uproot a root:// URL instead of a local file path, and it reads only the parts of the file it actually needs:

PYTHON 

import uproot

tthtobb_path = "root://eospublic.cern.ch//eos/opendata/cms/mc/RunIISummer20UL16NanoAODv9/ttHTobb_M125_TuneCP5_13TeV-powheg-pythia8/NANOAODSIM/106X_mcRun2_asymptotic_v17-v2/260000/410F948C-6956-2D45-A170-DE6431E02281.root"

tree = uproot.open(tthtobb_path)["Events"]
print("Number of events:", tree.num_entries)

OUTPUT 

Number of events: 174000

Nothing here gets downloaded to disk - uproot streams just the data it needs, which is why this works comfortably inside Colab’s storage limits.

The three files this lesson uses

This lesson uses three CMS Open Data files, one each from the ttHTobb, ttHTocc, and QCD_bcToE records, all confirmed to contain well over 100,000 events:

Dataset CERN Open Data record File used in this lesson Confirmed events
ttHTobb (Hbb signal) record 67645 410F948C-6956-2D45-A170-DE6431E02281.root 174,000
ttHTocc (Hcc signal) record 67651 5C12D3AA-9311-B840-BB5D-4155D7FF66E4.root 137,000
QCD_bcToE (background) record 63242 A133135A-C83E-D245-846F-210C7AD2D29C.root 345,045

Save each file’s full streaming path as a variable now, so you can reuse it in later episodes:

PYTHON 

TTHTOBB_PATH = "root://eospublic.cern.ch//eos/opendata/cms/mc/RunIISummer20UL16NanoAODv9/ttHTobb_M125_TuneCP5_13TeV-powheg-pythia8/NANOAODSIM/106X_mcRun2_asymptotic_v17-v2/260000/410F948C-6956-2D45-A170-DE6431E02281.root"

TTHTOCC_PATH = "root://eospublic.cern.ch//eos/opendata/cms/mc/RunIISummer20UL16NanoAODv9/ttHTocc_M125_TuneCP5_13TeV-powheg-pythia8/NANOAODSIM/106X_mcRun2_asymptotic_v17-v1/50000/5C12D3AA-9311-B840-BB5D-4155D7FF66E4.root"

QCD_BCTOE_PATH = "root://eospublic.cern.ch//eos/opendata/cms/mc/RunIISummer20UL16NanoAODv9/QCD_Pt_80to170_bcToE_TuneCP5_13TeV_pythia8/NANOAODSIM/106X_mcRun2_asymptotic_v17-v2/270000/A133135A-C83E-D245-846F-210C7AD2D29C.root"
Key Points
  • Colab does not preinstall uproot, fsspec-xrootd, awkward, or vector; install them with !pip install before running anything else in this lesson.
  • uproot.open() on a root:// URL streams a CMS file directly from CERN’s servers, without downloading it.
  • This lesson uses three specific files, one each from the ttHTobb, ttHTocc, and QCD_bcToE CERN Open Data records.
  • Always check tree.num_entries after opening a file - a much smaller count than expected means it’s the wrong file.